ReviewHealth science reports2026
Unveiling the Benefits of Artificial Intelligence in Individual, Organizational Management, and the Health/Sector System.
Review in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Unveiling the Benefits of Artificial Intelligence in Individual, Organizational Management, and the Health/Sector System.Health science reports · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) is transforming healthcare by improving care, efficiency, and cost benefit, yet limited research compares its benefits across individual, organizational, and system levels to guide effective integration. Aims: This review examines how the adoption of AI can benefit healthcare by improving individual outcomes, enhancing organizational efficiency, and strengthening the healthcare system. Methods: Two reviewers screened studies published up to December 2023 from four databases-a three-dimensional framework identified AI benefits for individuals, organizations, and the broader health sector. Results: A total of 92 articles met the inclusion criteria, showing AI provides meaningful benefits across all dimensions. The individual benefits dimension is precise but often context-specific, showing substantial gains in early detection, diagnosis, and monitoring. AI reduces the workload by 19%-50%, improves reading times by 21%-54%, and enhances cancer detection by 20% and treatment timing. The organizational benefits dimension encompasses AI-optimized workflows and cost reductions, enhancing efficiency in clinical settings and workflow management. The health sector system dimension shows the most substantial evidence, highlighting improved patient outcomes, workflow efficiency, data access, training, and overall system advancement. Despite these advantages, challenges remain regarding data integrity, patient safety, and privacy under strict healthcare regulations. Conclusion: AI offers benefits at all levels, with the most substantial evidence being at the system level, demonstrating clear improvements in patient care and workflow. Individual and organizational gains are promising, though more validation is needed. Future adoption should prioritize cost-benefit analysis and system-wide AI integration while evaluating impacts at all levels.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.